These data were compiled as a part of a landscape conservation design effort for the sagebrush biome and are the result of applying a spatially explicit model that assessed geographic patterns in Sagebrush Ecological Integrity and, a new quantitative measure of the intactness of sagebrush plant communities, used these results to identify Core Sagebrush Areas (CSAs), Growth Opportunity Areas (GOAs), and Other Rangeland Areas (ORAs). Our overall objective in this study was to characterize geographic patterns in ecological integrity of sagebrush ecosystems. These data represent the estimated integrity of sagebrush ecosystems, estimated from a spatial model that assigns high integrity in areas with abundant big sagebrush and perennial grass/forb cover and with minimal annual grass/forb cover, minimal conifers, and minimal human modification. This spatial model was applied over the entire sagebrush and was estimated for 5 historical time periods between 1998 and 2020, and for one future time period (2030-2060). For each time period, input data were derived from satellite imagery, and the spatial model used those input values to estimate Sagebrush Ecological Integrity. This approach to estimating ecological integrity was developed by consultation with experts from across the biome, allowing for the relationship between integrity and plant cover to vary among regions, as described in Doherty et al (2022). These data can be used to inform and prioritize conservation and restoration efforts across the sagebrush biome.

These data were compiled to provide a quantitative, spatially explicit estimate of ecological resilience and resistance (R&R) under ambient and projected future climate conditions. Objective of our study was to understand where and why climate change will alter the distribution of ecological resilience and resistance in the sagebrush biome throughout the 21st century. To accomplish this, we pursued four specific objectives: we estimated the new R&R indicators under future climate conditions and quantified changes from historical conditions; we developed a continuous R&R index that integrates probability information from the underlying predictive R&R models; we assessed the robustness of projected changes in R&R to uncertainty in future climate conditions. These data represent spatially-explicit estimates of ecological resilience and resistance (R&R; categorical indicators, probabilities, continuous indices) under ambient and downscaled projected historical and future climate conditions (historical, RCP 4.5, and RCP 8.5 CMIP5 scenarios). These data were created in rangelands and open woodlands across the sagebrush biome in 2023. These data were created by a collaboration between Northern Arizona University and the U.S. Geological Survey, Southwest Biological Science Center based on modeling which utilized predictive R&R models utilizing ecological and climate metrics which were based on soil properties (NRCS), ambient climate data (gridMET), and downscaled climate projections (MACAv2-METDATA). These data can be used to assess geographic patterns in resilience and resistance under ambient and projected future climate conditions.

These data were compiled to provide a quantitative, spatially explicit estimate of ecological resilience and resistance (R&R) under ambient and projected future climate conditions. Objective of our study was to understand where and why climate change will alter the distribution of ecological resilience and resistance in the sagebrush biome throughout the 21st century. To accomplish this, we pursued four specific objectives: we estimated the new R&R indicators under future climate conditions and quantified changes from historical conditions; we developed a continuous R&R index that integrates probability information from the underlying predictive R&R models; we assessed the robustness of projected changes in R&R to uncertainty in future climate conditions. These data represent spatially-explicit estimates of ecological resilience and resistance (R&R; categorical indicators, probabilities, continuous indices) under ambient and downscaled projected historical and future climate conditions (historical, RCP 4.5, and RCP 8.5 CMIP5 scenarios). These data were created in rangelands and open woodlands across the sagebrush biome in 2023. These data were created by a collaboration between Northern Arizona University and the U.S. Geological Survey, Southwest Biological Science Center based on modeling which utilized predictive R&R models utilizing ecological and climate metrics which were based on soil properties (NRCS), ambient climate data (gridMET), and downscaled climate projections (MACAv2-METDATA). These data can be used to assess geographic patterns in resilience and resistance under ambient and projected future climate conditions.

Sagebrush (Artemisia spp.) ecosystems provide critical habitat for the near-threatened Greater sage-grouse (Centrocercus urophasianus), and future loss of sagebrush habitat because of land use change and global climate change is of concern. We used a dynamic additive spatio-temporal model to estimate effects of climate (spring-summer temperatures and precipitation) on sagebrush cover dynamics at 32 sage-grouse management (core) areas in Wyoming, 1985-2018. We then use the fitted models to make probabilistic projections of sagebrush cover in each core area across three time intervals (2018-2040, 2041-2070, 2071-2100) and under three climate change scenarios and weighted averages of 18 Global Circulation Models (ssp126, ssp245, and ssp585), producing 351 netCDF files (USGS_SageCastWY.zip).

Sagebrush (Artemisia spp.) ecosystems provide critical habitat for the near-threatened Greater sage-grouse (Centrocercus urophasianus), and future loss of sagebrush habitat because of land use change and global climate change is of concern. We used a dynamic additive spatio-temporal model to estimate effects of climate (spring-summer temperatures and precipitation) on sagebrush cover dynamics at 32 sage-grouse management (core) areas in Wyoming, 1985-2018. We then use the fitted models to make probabilistic projections of sagebrush cover in each core area across three time intervals (2018-2040, 2041-2070, 2071-2100) and under three climate change scenarios and weighted averages of 18 Global Circulation Models (ssp126, ssp245, and ssp585), producing 351 netCDF files (USGS_SageCastWY.zip).

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Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management. We assessed potential future changes in sagebrush ecological integrity under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. We provide GeoTIFFs of biome-wide projections of future sagebrush ecological integrity (as described in Holdrege et al., 2024) under two representative concentration pathways (RCP4.5 and RCP8.5) and time-periods (2031-2060 and 2071-2100) and we provide these projections for multiple model assumptions. Additionally, this data set provides accompanying projections of three of the components of sagebrush ecological integrity, which are the Q (‘quality’, see Doherty et al., 2022) scores for sagebrush, perennial forbs and grasses, and annual forbs and grasses. Additional GeoTIFFs included provide current (2017-2020) Q scores and sagebrush ecological integrity, as well as projected changes in the extent of Core Sagebrush Areas, Growth Opportunity Areas, and Other Rangeland Areas.

Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management. We assessed potential future changes in sagebrush ecological integrity under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. We provide GeoTIFFs of biome-wide projections of future sagebrush ecological integrity (as described in Holdrege et al., 2024) under two representative concentration pathways (RCP4.5 and RCP8.5) and time-periods (2031-2060 and 2071-2100) and we provide these projections for multiple model assumptions. Additionally, this data set provides accompanying projections of three of the components of sagebrush ecological integrity, which are the Q (‘quality’, see Doherty et al., 2022) scores for sagebrush, perennial forbs and grasses, and annual forbs and grasses. Additional GeoTIFFs included provide current (2017-2020) Q scores and sagebrush ecological integrity, as well as projected changes in the extent of Core Sagebrush Areas, Growth Opportunity Areas, and Other Rangeland Areas.

Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management. We assessed potential future changes in sagebrush ecological integrity under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. We provide GeoTIFFs of biome-wide projections of future sagebrush ecological integrity (as described in Holdrege et al., 2024) under two representative concentration pathways (RCP4.5 and RCP8.5) and time-periods (2031-2060 and 2071-2100) and we provide these projections for multiple model assumptions. Additionally, this data set provides accompanying projections of three of the components of sagebrush ecological integrity, which are the Q (‘quality’, see Doherty et al., 2022) scores for sagebrush, perennial forbs and grasses, and annual forbs and grasses. Additional GeoTIFFs included provide current (2017-2020) Q scores and sagebrush ecological integrity, as well as projected changes in the extent of Core Sagebrush Areas, Growth Opportunity Areas, and Other Rangeland Areas.